from classy import Class
import os
import io
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import plotly.offline as py
py.init_notebook_mode()
from dautil.plot import iplot_column_slider
%matplotlib inline
LambdaCDM = Class()
from dautil.plot import iplot_column_slider
# optional: clear content of LambdaCDM (to reuse it for another model)
LambdaCDM.struct_cleanup()
# optional: reset parameters to default
LambdaCDM.empty()
kwargs = {
# background parameters
'H0': 67.32117,
'omega_b': 0.02238280,
'N_ur': 2.03066666667,
'omega_cdm': 0.1201075,
'N_ncdm': 1,
'omega_ncdm': 0.0006451439,
'YHe': 0.2454006,
'tau_reio': 0.05430842,
'n_s': 0.9660499,
'A_s': 2.100549e-09,
'non linear': 'halofit',
'output': 'tCl,pCl,lCl,mPk',
'lensing': 'yes',
# 'P_k_max_1/Mpc': 3.,
# 'l_max_scalars': 3000,
}
LambdaCDM.set(kwargs)
LambdaCDM.compute()
df = pd.DataFrame(LambdaCDM.lensed_cl())
df.set_index('ell', inplace=True)
ell = df.index.values.astype(np.int32)
df *= ((ell * (ell + 1)) * 0.5 / np.pi)[:, None]
df.columns = ['TT', 'EE', 'TE', 'BB', 'phiphi', 'TPhi']
# df *= 1.e12
df.head()
temp = LambdaCDM.get_thermodynamics()
df_thermo = pd.DataFrame(temp)
df_thermo.set_index('z', inplace=True)
df_thermo.tail()
py.iplot(iplot_column_slider(df_thermo))